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Вернуться к Custom and Distributed Training with TensorFlow

Отзывы учащихся о курсе Custom and Distributed Training with TensorFlow от партнера deeplearning.ai

4.8
звезд
Оценки: 288
Рецензии: 41

О курсе

In this course, you will: • Learn about Tensor objects, the fundamental building blocks of TensorFlow, understand the difference between the eager and graph modes in TensorFlow, and learn how to use a TensorFlow tool to calculate gradients. • Build your own custom training loops using GradientTape and TensorFlow Datasets to gain more flexibility and visibility with your model training. • Learn about the benefits of generating code that runs in graph mode, take a peek at what graph code looks like, and practice generating this more efficient code automatically with TensorFlow’s tools. • Harness the power of distributed training to process more data and train larger models, faster, get an overview of various distributed training strategies, and practice working with a strategy that trains on multiple GPU cores, and another that trains on multiple TPU cores. The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models....

Лучшие рецензии

VV

8 янв. 2022 г.

Another great course by Moroney sir. Loved how TF can be used to train models using different strategies. A great intro to the deep applications of TensorFlow

GJ

11 дек. 2021 г.

It was helpful to learn the details of the optimization by using GradientTape and manually updating the parameters for every iteration.

Фильтр по:

26–41 из 41 отзывов о курсе Custom and Distributed Training with TensorFlow

автор: Alexander Z

26 янв. 2021 г.

Thanks a lot! Greate course.

автор: Ed H N C

23 янв. 2021 г.

Its getting difficult.

автор: Jorge S

29 мар. 2021 г.

Best content around !

автор: M. A A

11 февр. 2021 г.

Great Instructor.

автор: Alysson M D O B

18 июля 2021 г.

Excelente curso!

автор: Alexander A

29 авг. 2021 г.

Great course!

автор: Javier B

6 июля 2021 г.

very nice

автор: Hoang D

26 дек. 2021 г.

useful

автор: Pramit D

10 февр. 2021 г.

75% of the course was good. Many of the topics were very interesting i.e. how default functions work and all. But the last weak was too hard and was not explained well. Again, it was suggested to use slack instead of discussion forums. But the mentors didn't respond to my query. Hence, the course is a good course and worth taking.

автор: Giora S

15 янв. 2021 г.

This course was much more detailed, I liked it. I hope there's a TF course down the road which really gets into all those numpy-like TF functions and APIs and how to use them for complex layers and losses.

автор: Stephen N

8 апр. 2021 г.

For a newbie (me) this course helps me to know something new but it's not much helpful for my current job now

автор: Pranjal J

1 янв. 2022 г.

The course provides under-the-hood insights of Keras APIs and gives in-depth review of native TF APIs

автор: Ruchen Z

24 янв. 2022 г.

W1 & W2 are amazing, W3 & W4 doesn't help much.

автор: Duc A L

19 окт. 2021 г.

Week 03 Grader is error

автор: H.S

18 февр. 2022 г.

A complete waste of time.

автор: Wendy W Y M

18 дек. 2020 г.

nothing here that I can't get from just reading the docs...